AMPL
A multistage stochastic programming model for the optimal bid of a wind producer
Wed, 07/11/2018 - 11:20 — admin| Publication Type | Conference Paper |
| Year of Publication | 2018 |
| Authors | F.-Javier Heredia; Marlyn D. Cuadrado; J.-Anton Sánchez |
| Conference Name | 23th International Symposium on Mathematical Programming |
| Conference Date | 01-06/07/2018 |
| Conference Location | Bordeaux |
| Type of Work | contributed presentation |
| Key Words | research; Battery energy storage systems; Electricity markets; Ancillary services market; Wind power generation; Virtual power plants; Stochastic programming |
| Abstract | Abstract: Battery Energy Storage Systems (BESS) can be used by wind producers to improve the operation of wind power plants (WPP) in electricity markets. Associating a wind power plant with a BESS (the so-called Virtual Power Plant (VPP)) provides utilities with a tool that converts uncertain wind power production into a dispatchable technology that can operate not only in spot and adjustment markets (day-ahead and intraday markets) but also in ancillary services markets that, up to now, were forbidden to non-dispatchable technologies. We present in this study a multi-stage stochastic programming model to find the optimal operation of a VPP in the day-ahead, intraday and secondary reserve markets while taking into account uncertainty in wind power generation and clearing prices (day-ahead, secondary reserve, intraday markets and system imbalances). A new forecasting procedure for the random variables involved in stochastic programming model has been developed. The forecasting model is based on Time Factor Series Analysis (TFSA) and gives suitable results while reducing the dimensionality of the forecasting mode. The quality of the scenario trees generated using the TFSA forecasting models with real electricity markets and wind production data has been analysed through multistage VSS. |
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On optimal participation in the electricity markets of wind power plants with battery energy storage systems
Tue, 05/15/2018 - 16:25 — admin| Publication Type | Journal Article |
| Year of Publication | 2018 |
| Authors | F.-Javier Heredia; Marlyn D. Cuadrado; Cristina Corchero |
| Journal Title | Computers and Operations Research |
| Volume | 96 |
| Pages | 316-329 |
| Journal Date | 08/2018 |
| Publisher | Elsevier |
| ISSN Number | 0305-0548 |
| Key Words | research; Battery energy storage systems; Electricity markets; Ancillary services market; Wind power generation; Virtual power plants; Stochastic programming; paper |
| Abstract | The recent cost reduction and technological advances in medium- to large-scale battery energy storage systems (BESS) makes these devices a true alternative for wind producers operating in electricity markets. Associating a wind power farm with a BESS (the so-called virtual power plant (VPP)) provides utilities with a tool that converts uncertain wind power production into a dispatchable technology that can operate not only in spot and adjustment markets (day-ahead and intraday markets) but also in ancillary services markets that, up to now, were forbidden to non-dispatchable technologies. What is more, recent studies have shown capital cost investment in BESS can be recovered only by means of such a VPP participating in the ancillary services markets. We present in this study a multi-stage stochastic programming model to find the optimal operation of a VPP in the day-ahead, intraday and secondary reserve markets while taking into account uncertainty in wind power generation and clearing prices (day-ahead, secondary reserve, intraday markets and system imbalances). A case study with real data from the Iberian electricity market is presented. |
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| DOI | 10.1016/j.cor.2018.03.004 |
| Preprint | http://hdl.handle.net/2117/118479 |
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Stochastic optimal generation bid to electricity markets with emissions risk constraints.
Tue, 01/30/2018 - 21:12 — admin| Publication Type | Journal Article |
| Year of Publication | 2018 |
| Authors | F.-Javier Heredia; Julián Cifuentes-Rubiano; Cristina Corchero |
| Journal Title | Journal of Environmental Management |
| Volume | 207 |
| Issue | 1 |
| Pages | 12 |
| Start Page | 432 |
| Journal Date | February 2018 |
| Publisher | Elsevier |
| ISSN Number | 0301-4797 |
| Key Words | research; OR in Energy; Stochastic Programming; Risk Management; Electricity market; Emissions reduction; paper |
| Abstract | There are many factors that influence the day-ahead market bidding strategies of a generation company (GenCo) within the framework of the current energy market. Environmental policy issues are giving rise to emission limitation that are becoming more and more important for fossil-fueled power plants, and these must be considered in their management. This work investigates the influence of the emissions reduction plan and the incorporation of the medium-term derivative commitments in the optimal generation bidding strategy for the day-ahead electricity market. Two different technologies have been considered: the high-emission technology of thermal coal units and the low-emission technology of combined cycle gas turbine units. The Iberian Electricity Market (MIBEL) and the Spanish National Emissions Reduction Plan (NERP) defines the environmental framework for dealing with the day-ahead market bidding strategies. To address emission limitations, we have extended some of the standard risk management methodologies developed for financial markets, such as Value-at-Risk (VaR) and Conditional Value-at-Risk (CVaR), thus leading to the new concept of Conditional Emission at Risk (CEaR). This study offers electricity generation utilities a mathematical model for determining the unit’s optimal generation bid to the wholesale electricity market such that it maximizes the long-term profits of the utility while allowing it to abide by the Iberian Electricity Market rules as well as the environmental restrictions set by the Spanish National Emissions Reduction Plan. We analyze the economic implications for a GenCo that includes the environmental restrictions of this National Plan as well as the NERP’s effects on the expected profits and the optimal generation bid. |
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| DOI | 10.1016/j.jenvman.2017.11.010 |
| Preprint | http://hdl.handle.net/2117/114024 |
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A Multistage Stochastic Programming Model for the Optimal Bid of Wind-BESS Virtual Power Plants to Electricity Markets
Sat, 12/16/2017 - 00:00 — admin| Publication Type | Conference Paper |
| Year of Publication | 2017 |
| Authors | F.-Javier Heredia; Marlyn D. Cuadrado; J.-Anton Sánchez |
| Conference Name | 4th International Conference on Optimization Methods and Software 2017 |
| Conference Date | 16-21/12/2017 |
| Conference Location | La Havana |
| Type of Work | Invited presentation |
| Key Words | multistage; VSS; wind-BESS VPP; wind power; energy storage; battery; research |
| Abstract | One of the objectives of the FOWGEN project (https://fowgem.upc.edu) was to study the economic feasibility and optimal operation of a wind-BESS Virtual Power Plant (VPP): In [1] an ex-post economic analysis shows the economic viability of a wind-BESS VPP thanks to the optimal operation in day-ahead and ancillary electricity markets; In [2] a new multi-stage stochastic programming model (WBVPP)for the optimal bid of a wind producer both in spot and ancillary services electricity markets is developed. The work presented here extends the study in [2] with a new methodology to treat the uncertainty, based in forecasting models, and the study of the quality of the stochastic solution. [1] F-Javier Heredia et al. Economic analysis of battery electric storage systems operating in electricity markets 12th International Conference on the European Energy Market (EEM15), 2015 DOI: 10.1109/EEM.2015.7216739. [2] F-Javier Heredia et al. On optimal participation in the electricity markets of wind power plants with battery energy storage system. Submitted, under second revision. 2017. |
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A multistage stochastic programming model for the optimal management of wind-BESS virtual power plants
Fri, 07/07/2017 - 10:16 — admin| Publication Type | Conference Paper |
| Year of Publication | 2017 |
| Authors | F.-Javier Heredia; Marlyn D. Cuadrado |
| Conference Name | WindFarms 2017 |
| Conference Date | 31/05-02/06/2017 |
| Conference Location | Madrid, Spain |
| Type of Work | Invited presentation |
| Key Words | research; wind farms; Ion-Li battery; multistage stochastic programming; stochastic programming |
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Optimal Supply Chain Strategy and Postponement Degree with 3D Printing
Mon, 07/18/2016 - 19:04 — admin| Publication Type | Conference Paper |
| Year of Publication | 2016 |
| Authors | Daniel Ramon Lumbierres; Asier Muguruza; Robert Gimeno Feu; Ping Guo; Mary Hamilton; Kiron Shastry; Sunny Webb; Joaquim Minguella; F.-Javier Heredia |
| Conference Name | 28th European Conference on Operational Research |
| Series Title | Conference Handbook |
| Pagination | 330 |
| Conference Date | 3-6/07/2016 |
| Conference Location | Poznan, Poland |
| Type of Work | contributed presentation. |
| Key Words | research; supply chain; 3D printing; stochastic programming; postponment; modeling; additive manufacturing |
| Abstract | In this contribution we would like to present the results of a research project developed by Accenture and BarcelonaTech aiming at studying the advantages of ultra-postponement with 3D printing using the analytical tools of operational research. In this project a new two-stage stochastic programming decision model has been developed to assess (a) the convenience of the introduction of 3D printing in any generic supply chain and (b) the optimal degree of postponement, the so called Customer Order Decoupling Point (CODP), assuming uncertainty in demand for multiple markets. To this end we propose the formulation of a generic supply chain through an oriented graph that represents all the alternative technologies that can be deployed, defined through a set of operations for manufacturing, assembly and distribution, each one characterized by a lead time and cost parameters. Based on this graph we develop a mixed integer two-stage stochastic program that finds the optimal manufacturing technology to meet the demand of each market, the optimal production quantity for each operation and the optimal CODP for each technology. The results obtained with several case studies from real manufacturing companies are presented and analyzed. |
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On the optimal participation in electricity markets of wind power plants with battery energy storage systems
Mon, 07/18/2016 - 18:43 — admin| Publication Type | Conference Paper |
| Year of Publication | 2016 |
| Authors | F.-Javier Heredia; Cristina Corchero; Marlyn D. Cuadrado |
| Conference Name | 28th European Conference on Operational Research |
| Series Title | Conference Handbook |
| Pagination | 322 |
| Conference Date | 3-6/07/2016 |
| Conference Location | Poznan, Poland |
| Type of Work | contributed presentation. |
| Key Words | research; VPP; wind generation; battery energy storage system; stochastic programming; electricity market; optimal bid |
| Abstract | The recent cost reduction and technologic advances in medium to large scale Battery Energy Storage Systems (BESS) makes these devices a real choice alternative for wind producers operating in electricity markets. The association of a wind power farm with a BESS (the so called Virtual Power Plant VPP) provides utilities with a tool to turn the uncertainty wind power production into a dispatchable technology enabled to operate not only in the spot and adjustment markets (day-ahead and intraday markets) but also in ancillary services markets that, up to now, was forbidden to non-dispatchable technologies. Even more, recent studies have shown that the capital cost investment in BESS can only be recovered through the participation of such a VPP in the ancillary services markets. We present in this study a stochastic programming model to find the optimal participation of a VPP to the day-ahead market and secondary reserve markets (the most relevant ancillary service market) where the uncertainty in wind power generation and markets prices (day-ahead ancillary services) has been considered. A case study with real data from the Iberian Electricity Market is presented. |
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Stochastic Optimal Bid to Electricity Markets with Emission Risk Constraints
Thu, 11/27/2014 - 21:20 — admin| Publication Type | Conference Paper |
| Year of Publication | 2014 |
| Authors | F.-Javier Heredia; Julián Cifuentes; Cristina Corchero |
| Conference Name | IFORS2014: 20th Conference of the International Federation of Operational Research Societies |
| Conference Date | 13-18/07/2014 |
| Conference Location | Barcelona |
| Type of Work | Invited presentation |
| Key Words | research; emission limits; risk; stochastic programming; day-ahead electricity market; combined cycle units |
| Abstract | This work allows investigating the influence of the emission reduction plan, and the incorporation of the derivatives medium-term commitments in the optimal generation bidding strategy to the day-ahead electricity market. Two different technologies have been considered: the coal thermal units, high-emission technology, and the combined cycle gas turbine units, low-emission technology. The Iberian Electricity Market (MIBEL) and the Spanish National Emission Reduction Plan (NERP) defines the environmental framework to deal with by the day-ahead market bidding strategies. To address emission limitations, some of the standard risk management methodologies developed for financial markets, such as Value-at-Risk (VaR) and Conditional Valueat- Risk (CVaR), have been extended giving rise to the new concept of Conditional Emission at Risk (CEaR). The economic implications for a GenCo of including the environmental restrictions of this National Plan are analyzed, and the effect of the NERP in the expected profits and optimal generation bid are analyzed. |
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